Self-potentials in partially saturated media: the importance of explicit modeling of electrode effects

TL;DR

This paper emphasizes the importance of explicitly modeling electrode effects in self-potential data analysis under partially saturated conditions, demonstrating improved agreement with experimental data and highlighting the need for better electrode modeling.

Contribution

It introduces a method to explicitly incorporate electrode effects into SP modeling, improving the accuracy of data interpretation under partially saturated conditions.

Findings

Explicit electrode modeling improves SP data agreement

Most published data likely include unaccounted electrode effects

Current SP theory is valid within modeling uncertainties

Abstract

Self-potential (SP) data are of interest to vadose zone hydrology because of their direct sensitivity to water flow and ionic transport. There is unfortunately little consensus in the literature about how to best model SP data under partially saturated conditions and different approaches (often supported by one laboratory data set alone) have been proposed. We argue herein that this lack of agreement can largely be traced to electrode effects that have not been properly taken into account. A series of drainage and imbibition experiments are considered, in which we find that previously proposed approaches to remove electrode effects are unlikely to provide adequate corrections. Instead, we explicitly model the electrode effects together with classical SP contributions using a flow and transport model. The simulated data agree overall with the observed SP signals and allow decomposing the different signal contributions to analyze them separately. By reviewing other published experimental data, we suggest that most of them include electrode effects that have not been properly taken into account. Our results suggest that previously presented SP theory works well when considering the modeling uncertainties presently associated with electrode effects. Additional work is warranted to not only develop suitable electrodes for laboratory experiments, but also to assure that associated electrode effects that appear inevitable in longer-term experiments are predictable, such that they can be incorporated in the modeling framework.